Influence of infection site and cultivar resistance on blackleg of canola in western Canada
Bibliographic record
Abstract
Blackleg, caused by the fungus Leptosphaeria maculans, remains a serious threat to canola production in Canada. This study aimed to identify critical infection pathways leading to stem colonization and to assess the role of quantitative resistance (QR) in affecting the infection process. Using point inoculations on specific leaf positions under both greenhouse and field conditions, we found that cotyledon inoculation consistently resulted in higher blackleg incidence and severity than inoculations on the 1st to 6th true leaves, corresponding with greater L. maculans DNA accumulation in stem tissues. Disease levels declined progressively with inoculation on upper leaves. In R-rated varieties, QR effectively suppressed stem infection – even from infected cotyledons. Field results generally aligned with greenhouse findings, although true-leaf inoculations caused slightly more disease under field conditions. Removal of non-inoculated cotyledons modestly reduced disease from true-leaf inoculations but not significantly. These results underscore the epidemiological importance of cotyledon infection, the protective effect of QR, and the value of cotyledon-based assays for QR screening and fungicide optimization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".